I am trying to get the multistream nvdcf tracker with yolov8n working but getting the following error. It works fine using the Nvidia resnet caffe model for multi stream and nvdcf tracker. It also works fine for a single stream yolov8n with multi-tracker. I am writing the code in C++.
m NvDsInferContextImpl::checkBackendParams() [UID = 1]: Backend has maxBatchSize 1 whereas 2 has been requested
0:05:17.864178821 1845 0x56206e548360 ERROR nvinfer gstnvinfer.cpp:632:gst_nvinfer_logger: NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::buildModel() [UID = 1]: deserialized backend context :/usr/src/app/build/model_b2_gpu0_fp16.engine failed to match config params
0:05:17.987313658 1845 0x56206e548360 ERROR nvinfer gstnvinfer.cpp:632:gst_nvinfer_logger: NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::generateBackendContext() [UID = 1]: build backend context failed
0:05:17.987342859 1845 0x56206e548360 ERROR nvinfer gstnvinfer.cpp:632:gst_nvinfer_logger: NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::initialize() [UID = 1]: generate backend failed, check config file settings
Hi,
I am trying to get the multistream nvdcf tracker with yolov8n working but getting the following error. It works fine using the Nvidia resnet caffe model for multi stream and nvdcf tracker. It also works fine for a single stream yolov8n with multi-tracker. I am writing the code in C++.
My configuration and cpp code is shown below.
`[property] gpu-id=0 net-scale-factor=0.0039215697906911373 model-color-format=0 model-engine-file=/usr/src/app/models/yolov8n/ppe.engine onnx-file=/usr/src/app/models/yolov8n/yolov8n.onnx labelfile-path=/usr/src/app/models/yolov8n/labels.txt batch-size=1 network-mode=2 num-detected-classes=7 force-implicit-batch-dim=1 interval=0 gie-unique-id=1 process-mode=1 network-type=0 cluster-mode=2 maintain-aspect-ratio=1 symmetric-padding=1 parse-bbox-func-name=NvDsInferParseYolo custom-lib-path=/opt/nvidia/deepstream/deepstream/sources/DeepStream-Yolo/nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so engine-create-func-name=NvDsInferYoloCudaEngineGet
[class-attrs-all] nms-iou-threshold=0.45 pre-cluster-threshold=0.25 topk=300 detected-min-w=20 detected-min-h=20
`